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lm5-2b8-55b-c4
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#!/bin/bash
#SBATCH --exclude=nid005159
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=32
#SBATCH --mem=256G
#SBATCH -p small-g
#SBATCH -t 2-0:00:00
#SBATCH --gpus-per-node=mi250:1
#SBATCH --exclusive=user
#SBATCH --hint=nomultithread
#SBATCH --account=project_462000119
#SBATCH -o logs/%j.out
#SBATCH -e logs/%j.err

# if run without sbatch, invoke here
if [ -z $SLURM_JOB_ID ]; then
    mkdir -p logs
    sbatch "$0"
    exit
fi

set -euo pipefail

# symlink logs/latest_eval.out and logs/latest_eval.err
ln -f -s $SLURM_JOB_ID.out logs/latest_eval.out
ln -f -s $SLURM_JOB_ID.err logs/latest_eval.err

source /pfs/lustrep4/scratch/project_462000119/muennighoff/nov-2022-bettercom/venv/bin/activate

echo "START TIME: $(date)"

# defining the right environment variables
export HF_DATASETS_OFFLINE=1
export HF_DATASETS_CACHE=/scratch/project_462000119/ds_cache

# Converted transformer checkpoint
MODEL_CKPT=/pfs/lustrep4/scratch/project_462000119/muennighoff/nov-2022-bettercom/lm1-2b8-55b-oscar-repetitions/2b855b18bc4/transformers
MODEL_CKPT=/pfs/lustrep4/scratch/project_462000119/muennighoff/nov-2022-bettercom/lm1-2b8-55b-oscar-repetitions/2b855b9boscar/transformers
MODEL_CKPT=/pfs/lustrep4/scratch/project_462000119/muennighoff/nov-2022-bettercom/lm1-2b8-55b-c4py/2b855b90c4py/transformers
#MODEL_CKPT=/pfs/lustrep4/scratch/project_462000119/muennighoff/nov-2022-bettercom/lm1-2b8-55b-realtasky/transformers
MODEL_CKPT=/pfs/lustrep4/scratch/project_462000119/muennighoff/dec-2022-ul2/lm3-2b8-55b-c4/transformers
TOKENIZER=/pfs/lustrep4/scratch/project_462000119/muennighoff/dec-2022-ul2/gpt2

cd /pfs/lustrep4/scratch/project_462000119/muennighoff/nov-2022-bettercom/bigscience/lm-evaluation-harness

# WMT19 ZH-EN does not work
DATASETS_AND_CONFIGS=(
GEM/wiki_lingua_en,"tldr_en"
gem_xsum,"article_DOC_summary"
GEM/web_nlg_en,"PALM_prompt"
e2e_nlg_cleaned,"generate_text_restaurant"
)

DATASET_AND_CONFIG=${DATASETS_AND_CONFIGS[$SLURM_ARRAY_TASK_ID]}
#echo $ARGUMENT

IFS=',' read dataset_name template_name <<< "${DATASET_AND_CONFIG}"

# Use this fork of lm-eval: https://github.com/bigscience-workshop/lm-evaluation-harness/pull/109
python main.py \
    --model_api_name 'hf-causal' \
    --model_args pretrained=$MODEL_CKPT,use_accelerate=True,tokenizer=$TOKENIZER,dtype=bfloat16 \
    --device cuda \
    --batch_size 16 \
    --no_tracking \
    --task_name $dataset_name \
    --template_names $template_name \
    --bootstrap_iters 10 \
    --limit 3000 \
    --num_fewshot 1

echo "END TIME: $(date)"